System and method for dynamically partitioning processing across plurality of heterogeneous processors

ABSTRACT

A program is into at least two object files: one object file for each of the supported processor environments. During compilation, code characteristics, such as data locality, computational intensity, and data parallelism, are analyzed and recorded in the object file. During run time, the code characteristics are combined with runtime considerations, such as the current load on the processors and the size of the data being processed, to arrive at an overall value. The overall value is then used to determine which of the processors will be assigned the task. The values are assigned based on the characteristics of the various processors. For example, if one processor is better at handling intensive computations against large streams of data, programs that are highly computationally intensive and process large quantities of data are weighted in favor of that processor. The corresponding object is then loaded and executed on the assigned processor.

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates in general to a system and method for partitioning processing across heterogeneous processors. More particularly, the present invention relates to a system and method selecting one of the heterogeneous processors to run an object based upon computational and load considerations.

2. Description of the Related Art

Computer systems are becoming more and more complex. The computer industry typically doubles the performance of a computer system every 18 months (i.e. personal computer, PDA, gaming console). In order for the computer industry to accomplish this task, the semiconductor industry produces integrated circuits that double in performance every 18 months. A computer system uses integrated circuits for particular functions based upon the integrated circuits' architecture. Two fundamental architectures are 1) microprocessor-based and 2) digital signal processor-based.

An integrated circuit with a microprocessor-based architecture is typically used to handle control operations whereas an integrated circuit with a digital signal processor-based architecture is typically designed to handle signal-processing manipulations (i.e. mathematical operations). As technology evolves, the computer industry and the semiconductor industry realized the importance of using both architectures, or processor types, in a computer system design.

Software is another element in a computer system that has been evolving alongside integrated circuit evolution. A software developer writes code in a manner that corresponds to the processor type that executes the code. For example, a processor has a particular number of registers and a particular number of arithmetic logic units (ALUs) whereby the software developer designs code to most effectively use the registers and the ALUs. In addition, the compiler used by the software developer is traditionally designed to compile code to operate on a specific processor environment. This traditionally limits the developer's function to operate on a single environment. At runtime, the compiled code is loaded and executed by the processor.

As the semiconductor industry incorporates multiple processor types onto a single device, a challenge found for the software developer is to write code based upon a multiple processor type architecture. A software developer's code includes a plurality of subtasks whereby each subtask may be designed to run on a particular processor type. For example, a subtask that manages “control” operations is better suited to run on a microprocessor.

However, there are many subtasks that run adequately on either processor type. In this case, the subtask would be best run on a processor that is not heavily loaded at a particular time. A challenge found, however, is that existing art requires a software developer to identify a processor type at compilation, not at runtime. A notable exception to this, however, is an environment that uses a “virtual machine” (such as a Java Virtual Machine (JVM), so that the applications are compiled to operate using the virtual machine with each supported operating environment employing a different version of the virtual machine that operates on the operating environment. A challenge of virtual machines, however, is that they require system resources to manage the virtual environment (i.e., a garbage-collected heap, etc.) and, because the application code is being performed by a virtual machine rather than directly by a processor, virtual machine code is traditionally slower and less efficient than code that executes directly on a processor.

What is needed, therefore, is a system and method to compile source code into a plurality of object files adapted to execute on a plurality of processor operating environments. What is further needed is a system and method that selects the object file to execute based upon current computer system operational considerations.

SUMMARY

A system and method are provided to partition a computational problem based upon available processing resources in a heterogeneous processing environment and suitability to task. SPUs are faster processors that can process large amounts of data very quickly, while PUs have a richer instruction set but are less efficient at processing a large amount of data. The breaking of the problem can be performed dynamically at run time or can be performed statically (i.e., chosen by the programmer when writing the application). Both processors share a common memory map and both processors can fetch virtual addresses and can fetch data from the cache. In addition, both the SPU and PU go through the same memory address translation.

A software developer compiles a program into at least two object files—one object file for each of the supported processor environments. During compilation, code characteristics, such as data locality, computational intensity, and data parallelism, are analyzed and recorded in the object file. During run time, the code characteristics are combined with runtime considerations, such as the current load on the processors and the size of the data being processed, to arrive at an overall value. The overall value is then used to determine which of the processors will be assigned the task. The values are assigned based on the characteristics of the various processors. For example, if one processor is better at handling intensive computations against large streams of data, programs that are highly computationally intensive and process large quantities of data are weighted in favor of that processor. The corresponding object is then loaded and executed on the assigned processor.

The foregoing is a summary and thus contains, by necessity, simplifications, generalizations, and omissions of detail; consequently, those skilled in the art will appreciate that the summary is illustrative only and is not intended to be in any way limiting. Other aspects, inventive features, and advantages of the present invention, as defined solely by the claims, will become apparent in the non-limiting detailed description set forth below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention may be better understood, and its numerous objects, features, and advantages made apparent to those skilled in the art by referencing the accompanying drawings. The use of the same reference symbols in different drawings indicates similar or identical items.

FIG. 1 illustrates—the overall architecture of a computer network in accordance with the present invention;

FIG. 2 is a diagram illustrating the structure of a processing unit (PU) in accordance with the present invention;

FIG. 3 is a diagram illustrating the structure of a broadband engine (BE) in accordance with the present invention;

FIG. 4 is a diagram illustrating the structure of an synergistic processing unit (SPU) in accordance with the present invention;

FIG. 5 is a diagram illustrating the structure of a processing unit, visualizer (VS) and an optical interface in accordance with the present invention;

FIG. 6 is a diagram illustrating one combination of processing units in accordance with the present invention;

FIG. 7 illustrates another combination of processing units in accordance with the present invention;

FIG. 8 illustrates yet another combination of processing units in accordance with the present invention;

FIG. 9 illustrates yet another combination of processing units in accordance with the present invention;

FIG. 10 illustrates yet another combination of processing units in accordance with the present invention;

FIG. 11A illustrates the integration of optical interfaces within a chip package in accordance with the present invention;

FIG. 11B is a diagram of one configuration of processors using the optical interfaces of FIG. 11A;

FIG. 11C is a diagram of another configuration of processors using the optical interfaces of FIG. 11A;

FIG. 12A illustrates the structure of a memory system in accordance with the present invention;

FIG. 12B illustrates the writing of data from a first broadband engine to a second broadband engine in accordance with the present invention;

FIG. 13 is a diagram of the structure of a shared memory for a processing unit in accordance with the present invention;

FIG. 14A illustrates one structure for a bank of the memory shown in FIG. 13;

FIG. 14B illustrates another structure for a bank of the memory shown in FIG. 13;

FIG. 15 illustrates a structure for a direct memory access controller in accordance with the present invention;

FIG. 16 illustrates an alternative structure for a direct memory access controller in accordance with the present invention;

FIGS. 17-31 illustrate the operation of data synchronization in accordance with the present invention;

FIG. 32 is a three-state memory diagram illustrating the various states of a memory location in accordance with the data synchronization scheme of the-present invention;

FIG. 33 illustrates the structure of a key control table for a hardware sandbox in accordance with the present invention;

FIG. 34 illustrates a scheme for storing memory access keys for a hardware sandbox in accordance with the present invention;

FIG. 35 illustrates the structure of a memory access control table for a hardware sandbox in accordance with the present invention;

FIG. 36 is a flow diagram of the steps for accessing a memory sandbox using the key control table of FIG. 33 and the memory access control table of FIG. 35;

FIG. 37 illustrates the structure of a software cell in accordance with the present invention;

FIG. 38 is a flow diagram of the steps for issuing remote procedure calls to SPUs in accordance with the present invention;

FIG. 39 illustrates the structure of a dedicated pipeline for processing streaming data in accordance with the present invention;

FIG. 40 is a flow diagram of the steps performed by the dedicated pipeline of FIG. 39 in the processing of streaming data in accordance with the present invention;

FIG. 41 illustrates an alternative structure for a dedicated pipeline for the processing of streaming data in accordance with the present invention;

FIG. 42 illustrates a scheme for an absolute timer for coordinating the parallel processing of applications and data by SPUs in accordance with the present invention;

FIG. 43 is a flowchart showing the steps taken to compile a given source code into object files adapted to execute in a heterogeneous processor environment;

FIG. 44 is a flowchart showing steps taken by a loader in the heterogeneous processor environment selecting in selecting one of the heterogeneous processor types to execute an object file;

FIG. 45 is a flowchart showing steps taken by the loader in the heterogeneous processor environment identifying a preferred processor for a given task;

FIG. 46 is a flowchart showing steps taken by an SPU processor in executing an object file scheduled to it by the loader; and

FIG. 47 is a block diagram illustrating a processing element having a main processor and a plurality of secondary processors sharing a system memory.

DETAILED DESCRIPTION

The following is intended to provide a detailed description of an example of the invention and should not be taken to be limiting of the invention itself. Rather, any number of variations may fall within the scope of the invention which is defined in the claims following the description.

The overall architecture for a computer system 101 in accordance with the present invention is shown in FIG. 1.

As illustrated in this figure, system 101 includes network 104 to which is connected a plurality of computers and computing devices. Network 104 can be a LAN, a global network, such as the Internet, or any other computer network.

The computers and computing devices connected to network 104 (the network's “members”) include, e.g., client computers 106, server computers 108, personal digital assistants (PDAs) 110, digital television (DTV) 112 and other wired or wireless computers and computing devices. The processors employed by the members of network 104 are constructed from the same common computing module. These processors also preferably all have the same ISA and perform processing in accordance with the same instruction set. The number of modules included within any particular processor depends upon the processing power required by that processor.

For example, since servers 108 of system 101 perform more processing of data and applications than clients 106, servers 108 contain more computing modules than clients 106. PDAs 110, on the other hand, perform the least amount of processing. PDAs 110, therefore, contain the smallest number of computing modules. DTV 112 performs a level of processing between that of clients 106 and servers 108. DTV 112, therefore, contains a number of computing modules between that of clients 106 and servers 108. As discussed below, each computing module contains a processing controller and a plurality of identical processing units for performing parallel processing of the data and applications transmitted over network 104.

This homogeneous configuration for system 101 facilitates adaptability, processing speed and processing efficiency. Because each member of system 101 performs processing using one or more (or some fraction) of the same computing module, the particular computer or computing device performing the actual processing of data and applications is unimportant. The processing of a particular application and data, moreover, can be shared among the network's members. By uniquely identifying the cells comprising the data and applications processed by system 101 throughout the system, the processing results can be transmitted to the computer or computing device requesting the processing regardless of where this processing occurred. Because the modules performing this processing have a common structure and employ a common ISA, the computational burdens of an added layer of software to achieve compatibility among the processors is avoided. This architecture and programming model facilitates the processing speed necessary to execute, e.g., real-time, multimedia applications. To take further advantage of the processing speeds and efficiencies facilitated by system 101, the data and applications processed by this system are packaged into uniquely identified, uniformly formatted software cells 102. Each software cell 102 contains, or can contain, both applications and data. Each software cell also contains an ID to globally identify the cell throughout network 104 and system 101. This uniformity of structure for the software cells, and the software cells' unique identification throughout the network, facilitates the processing of applications and data on any computer or computing device of the network. For example, a client 106 may formulate a software cell 102 but, because of the limited processing capabilities of client 106, transmit this software cell to a server 108 for processing. Software cells can migrate, therefore, throughout network 104 for processing on the basis of the availability of processing resources on the network.

The homogeneous structure of processors and software cells of system 101 also avoids many of the problems of today's heterogeneous networks. For example, inefficient programming models which seek to permit processing of applications on any ISA using any instruction set, e.g., virtual machines such as the Java virtual machine, are avoided. System 101, therefore, can implement broadband processing far more effectively and efficiently than today's networks.

The basic processing module for all members of network 104 is the processing unit (PU). FIG. 2 illustrates the structure of a PU. As shown in this figure, PE 201 comprises a processing unit (PU) 203, a direct memory access controller (DMAC) 205 and a plurality of synergistic processing units (SPUs), namely, SPU 207, SPU 209, SPU 211, SPU 213, SPU 215, SPU 217, SPU 219 and SPU 221. A local PE bus 223 transmits data and applications among the SPUs, DMAC 205 and PU 203. Local PE bus 223 can have, e.g., a conventional architecture or be implemented as a packet switch network. Implementation as a packet switch network, while requiring more hardware, increases available bandwidth.

PE 201 can be constructed using various methods for implementing digital logic. PE 201 preferably is constructed, however, as a single integrated circuit employing a complementary metal oxide semiconductor (CMOS) on a silicon substrate. Alternative materials for substrates include gallium arsinide, gallium aluminum arsinide and other so-called III-B compounds employing a wide variety of dopants. PE 201 also could be implemented using superconducting material, e.g., rapid single-flux-quantum (RSFQ) logic.

PE 201 is closely associated with a dynamic random access memory (DRAM) 225 through a high bandwidth memory connection 227. DRAM 225 functions as the main memory for PE 201. Although a DRAM 225 preferably is a dynamic random access memory, DRAM 225 could be implemented using other means, e.g., as a static random access memory (SRAM), a magnetic random access memory (MRAM), an optical memory or a holographic memory. DMAC 205 facilitates the transfer of data between DRAM 225 and the SPUs and PU of PE 201. As further discussed below, DMAC 205 designates for each SPU an exclusive area in DRAM 225 into which only the SPU can write data and from which only the SPU can read data. This exclusive area is designated a “sandbox.”

PU 203 can be, e.g., a standard processor capable of stand-alone processing of data and applications. In operation, PU 203 schedules and orchestrates the processing of data and applications by the SPUs. The SPUs preferably are single instruction, multiple data (SIMD) processors. Under the control of PU 203, the SPUs perform the processing of these data and applications in a parallel and independent manner. DMAC 205 controls accesses by PU 203 and the SPUs to the data and applications stored in the shared DRAM 225. Although PE 201 preferably includes eight SPUs, a greater or lesser number of SPUs can be employed in a PU depending upon the processing power required. Also, a number of PUs, such as PE 201, may be joined or packaged together to provide enhanced processing power.

For example, as shown in FIG. 3, four PUs may be packaged or joined together, e.g., within one or more chip packages, to form a single processor for a member of network 104. This configuration is designated a broadband engine (BE). As shown in FIG. 3, BE 301 contains four PUs, namely, PE 303, PE 305, PE 307 and PE 309. Communications among these PUs are over BE bus 311. Broad bandwidth memory connection 313 provides communication between shared DRAM 315 and these PUs. In lieu of BE bus 311, communications among the PUs of BE 301 can occur through DRAM 315 and this memory connection.

Input/output (I/O) interface 317 and external bus 319 provide communications between broadband engine 301 and the other members of network 104. Each PU of BE 301 performs processing of data and applications in a parallel and independent manner analogous to the parallel and independent processing of applications and data performed by the SPUs of a PU.

FIG. 4 illustrates the structure of an SPU. SPU 402 includes local memory 406, registers 410, four floating point units 412 and four integer units 414. Again, however, depending upon the processing power required, a greater or lesser number of floating points units 412 and integer units 414 can be employed. In a preferred embodiment, local memory 406 contains 128 kilobytes of storage, and the capacity of registers 410 is 128.times.128 bits. Floating point units 412 preferably operate at a speed of 32 billion floating point operations per second (32 GFLOPS), and integer units 414 preferably operate at a speed of 32 billion operations per second (32 GOPS).

Local memory 406 is not a cache memory. Local memory 406 is preferably constructed as an SRAM. Cache coherency support for an SPU is unnecessary. A PU may require cache coherency support for direct memory accesses initiated by the PU. Cache coherency support is not required, however, for direct memory accesses initiated by an SPU or for accesses from and to external devices.

SPU 402 further includes bus 404 for transmitting applications and data to and from the SPU. In a preferred embodiment, this bus is 1,024 bits wide. SPU 402 further includes internal busses 408, 420 and 418. In a preferred embodiment, bus 408 has a width of 256 bits and provides communications between local memory 406 and registers 410. Busses 420 and 418 provide communications between, respectively, registers 410 and floating point units 412, and registers 410 and integer units 414. In a preferred embodiment, the width of busses 418 and 420 from registers 410 to the floating point or integer units is 384 bits, and the width of busses 418 and 420 from the floating point or integer units to registers 410 is 128 bits. The larger width of these busses from registers 410 to the floating point or integer units than from these units to registers 410 accommodates the larger data flow from registers 410 during processing. A maximum of three words are needed for each calculation. The result of each calculation, however, normally is only one word.

FIGS. 5-10 further illustrate the modular structure of the processors of the members of network 104. For example, as shown in FIG. 5, a processor may comprise a single PU 502. As discussed above, this PU typically comprises a PU, DMAC and eight SPUs. Each SPU includes local storage (LS). On the other hand, a processor may comprise the structure of visualizer (VS) 505. As shown in FIG. 5, VS 505 comprises PU 512, DMAC 514 and four SPUs, namely, SPU 516, SPU 518, SPU 520 and SPU 522. The space within the chip package normally occupied by the other four SPUs of a PU is occupied in this case by pixel engine 508, image cache 510 and cathode ray tube controller (CRTC) 504. Depending upon the speed of communications required for PU 502 or VS 505, optical interface 506 also may be included on the chip package.

Using this standardized, modular structure, numerous other variations of processors can be constructed easily and efficiently. For example, the processor shown in FIG. 6 comprises two chip packages, namely, chip package 602 comprising a BE and chip package 604 comprising four VSs. Input/output (I/O) 606 provides an interface between the BE of chip package 602 and network 104. Bus 608 provides communications between chip package 602 and chip package 604. Input output processor (IOP) 610 controls the flow of data into and out of I/O 606. I/O 606 may be fabricated as an application specific integrated circuit (ASIC). The output from the VSs is video signal 612.

FIG. 7 illustrates a chip package for a BE 702 with two optical interfaces 704 and 706 for providing ultra high speed communications to the other members of network 104 (or other chip packages locally connected). BE 702 can function as, e.g., a server on network 104.

The chip package of FIG. 8 comprises two PEs 802 and 804 and two VSs 806 and 808. An I/O 810 provides an interface between the chip package and network 104. The output from the chip package is a video signal. This configuration may function as, e.g., a graphics work station.

FIG. 9 illustrates yet another configuration. This configuration contains one-half of the processing power of the configuration illustrated in FIG. 8. Instead of two PUs, one PE 902 is provided, and instead of two VSs, one VS 904 is provided. I/O 906 has one-half the bandwidth of the I/O illustrated in FIG. 8. Such a processor also may function, however, as a graphics work station.

A final configuration is shown in FIG. 10. This processor consists of only a single VS 1002 and an I/O 1004. This configuration may function as, e.g., a PDA.

FIG. 11A illustrates the integration of optical interfaces into a chip package of a processor of network 104. These optical interfaces convert optical signals to electrical signals and electrical signals to optical signals and can be constructed from a variety of materials including, e.g., gallium arsinide, aluminum gallium arsinide, germanium and other elements or compounds. As shown in this figure, optical interfaces 1104 and 1106 are fabricated on the chip package of BE 1102. BE bus 1108 provides communication among the PUs of BE 1102, namely, PE 1110, PE 1112, PE 1114, PE 1116, and these optical interfaces. Optical interface 1104 includes two ports, namely, port 1118 and port 1120, and optical interface 1106 also includes two ports, namely, port 1122 and port 1124. Ports 1118, 1120, 1122 and 1124 are connected to, respectively, optical wave guides 1126, 1128, 1130 and 1132. Optical signals are transmitted to and from BE 1102 through these optical wave guides via the ports of optical interfaces 1104 and 1106 plurality of BEs can be connected together in various configurations using such optical wave guides and the four optical ports of each BE. For example, as shown in FIG. 11B, two or more BEs, e.g., BE 1152, BE 1154 and BE 1156, can be connected serially through such optical ports. In this example, optical interface 1166 of BE 1152 is connected through its optical ports to the optical ports of optical interface 1160 of BE 1154. In a similar manner, the optical ports of optical interface 1162 on BE 1154 are connected to the optical ports of optical interface 1164 of BE 1156.

A matrix configuration is illustrated in FIG. 11C. In this configuration, the optical interface of each BE is connected to two other BEs. As shown in this figure, one of the optical ports of optical interface 1188 of BE 1172 is connected to an optical port of optical interface 1182 of BE 1176. The other optical port of optical interface 1188 is connected to an optical port of optical interface 1184 of BE 1178. In a similar manner, one optical port of optical interface 1190 of BE 1174 is connected to the other optical port of optical interface 1184 of BE 1178. The other optical port of optical interface 1190 is connected to an optical port of optical interface 1186 of BE 1180. This matrix configuration can be extended in a similar manner to other BEs.

Using either a serial configuration or a matrix configuration, a processor for network 104 can be constructed of any desired size and power. Of course, additional ports can be added to the optical interfaces of the BEs, or to processors having a greater or lesser number of PUs than a BE, to form other configurations.

FIG. 12A illustrates the control system and structure for the DRAM of a BE. A similar control system and structure is employed in processors having other sizes and containing more or less PUs. As shown in this figure, a cross-bar switch connects each DMAC 1210 of the four PUs comprising BE 1201 to eight bank controls 1206. Each bank control 1206 controls eight banks 1208 (only four are shown in the figure) of DRAM 1204. DRAM 1204, therefore, comprises a total of sixty-four banks. In a preferred embodiment, DRAM 1204 has a capacity of 64 megabytes, and each bank has a capacity of 1 megabyte. The smallest addressable unit within each bank, in this preferred embodiment, is a block of 1024 bits.

BE 1201 also includes switch unit 1212. Switch unit 1212 enables other SPUs on BEs closely coupled to BE 1201 to access DRAM 1204. A second BE, therefore, can be closely coupled to a first BE, and each SPU of each BE can address twice the number of memory locations normally accessible to an SPU. The direct reading or writing of data from or to the DRAM of a first BE from or to the DRAM of a second BE can occur through a switch unit such as switch unit 1212.

For example, as shown in FIG. 12B, to accomplish such writing, the SPU of a first BE, e.g., SPU 1220 of BE 1222, issues a write command to a memory location of a DRAM of a second BE, e.g., DRAM 1228 of BE 1226 (rather than, as in the usual case, to DRAM 1224 of BE 1222). DMAC 1230 of BE 1222 sends the write command through cross-bar switch 1221 to bank control 1234, and bank control 1234 transmits the command to an external port 1232 connected to bank control 1234. DMAC 1238 of BE 1226 receives the write command and transfers this command to switch unit 1240 of BE 1226. Switch unit 1240 identifies the DRAM address contained in the write command and sends the data for storage in this address through bank control 1242 of BE 1226 to bank 1244 of DRAM 1228. Switch unit 1240, therefore, enables both DRAM 1224 and DRAM 1228 to function as a single memory space for the SPUs of BE 1226.

FIG. 13 shows the configuration of the sixty-four banks of a DRAM. These banks are arranged into eight rows, namely, rows 1302, 1304, 1306, 1308, 1310, 1312, 1314 and 1316 and eight columns, namely, columns 1320, 1322, 1324, 1326, 1328, 1330, 1332 and 1334. Each row is controlled by a bank controller. Each bank controller, therefore, controls eight megabytes of memory.

FIGS. 14A and 14B illustrate different configurations for storing and accessing the smallest addressable memory unit of a DRAM, e.g., a block of 1024 bits. In FIG. 14A, DMAC 1402 stores in a single bank 1404 eight 1024 bit blocks 1406. In FIG. 14B, on the other hand, while DMAC 1412 reads and writes blocks of data containing 1024 bits, these blocks are interleaved between two banks, namely, bank 1414 and bank 1416. Each of these banks, therefore, contains sixteen blocks of data, and each block of data contains 512 bits. This interleaving can facilitate faster accessing of the DRAM and is useful in the processing of certain applications.

FIG. 15 illustrates the architecture for a DMAC 1504 within a PE. As illustrated in this figure, the structural hardware comprising DMAC 1506 is distributed throughout the PE such that each SPU 1502 has direct access to a structural node 1504 of DMAC 1506. Each node executes the logic appropriate for memory accesses by the SPU to which the node has direct access.

FIG. 16 shows an alternative embodiment of the DMAC, namely, a non-distributed architecture. In this case, the structural hardware of DMAC 1606 is centralized. SPUs 1602 and PU 1604 communicate with DMAC 1606 via local PE bus 1607. DMAC 1606 is connected through a cross-bar switch to a bus 1608. Bus 1608 is connected to DRAM 1610.

As discussed above, all of the multiple SPUs of a PU can independently access data in the shared DRAM. As a result, a first SPU could be operating upon particular data in its local storage at a time during which a second SPU requests these data. If the data were provided to the second SPU at that time from the shared DRAM, the data could be invalid because of the first SPU's ongoing processing which could change the data's value. If the second processor received the data from the shared DRAM at that time, therefore, the second processor could generate an erroneous result. For example, the data could be a specific value for a global variable. If the first processor changed that value during its processing, the second processor would receive an outdated value. A scheme is necessary, therefore, to synchronize the SPUs' reading and writing of data from and to memory locations within the shared DRAM. This scheme must prevent the reading of data from a memory location upon which another SPU currently is operating in its local storage and, therefore, which are not current, and the writing of data into a memory location storing current data.

To overcome these problems, for each addressable memory location of the DRAM, an additional segment of memory is allocated in the DRAM for storing status information relating to the data stored in the memory location. This status information includes a full/empty (F/E) bit, the identification of an SPU (SPU ID) requesting data from the memory location and the address of the SPU's local storage (LS address) to which the requested data should be read. An addressable memory location of the DRAM can be of any size. In a preferred embodiment, this size is 1024 bits.

The setting of the F/E bit to 1 indicates that the data stored in the associated memory location are current. The setting of the F/E bit to 0, on the other hand, indicates that the data stored in the associated memory location are not current. If an SPU requests the data when this bit is set to 0, the SPU is prevented from immediately reading the data. In this case, an SPU ID identifying the SPU requesting the data, and an LS address identifying the memory location within the local storage of this SPU to which the data are to be read when the data become current, are entered into the additional memory segment.

An additional memory segment also is allocated for each memory location within the local storage of the SPUs. This additional memory segment stores one bit, designated the “busy bit.” The busy bit is used to reserve the associated LS memory location for the storage of specific data to be retrieved from the DRAM. If the busy bit is set to 1 for a particular memory location in local storage, the SPU can use this memory location only for the writing of these specific data. On the other hand, if the busy bit is set to 0 for a particular memory location in local storage, the SPU can use this memory location for the writing of any data.

Examples of the manner in which the F/E bit, the SPU ID, the LS address and the busy bit are used to synchronize the reading and writing of data from and to the shared DRAM of a PU are illustrated in FIGS. 17-31.

As shown in FIG. 17, one or more PUs, e.g., PE 1720, interact with DRAM 1702. PE 1720 includes SPU 1722 and SPU 1740. SPU 1722 includes control logic 1724, and SPU 1740 includes control logic 1742. SPU 1722 also includes local storage 1726. This local storage includes a plurality of addressable memory locations 1728. SPU 1740 includes local storage 1744, and this local storage also includes a plurality of addressable memory locations 1746. All of these addressable memory locations preferably are 1024 bits in size.

An additional segment of memory is associated with each LS addressable memory location. For example, memory segments 1729 and 1734 are associated with, respectively, local memory locations 1731 and 1732, and memory segment 1752 is associated with local memory location 1750. A “busy bit,” as discussed above, is stored in each of these additional memory segments. Local memory location 1732 is shown with several Xs to indicate that this location contains data.

DRAM 1702 contains a plurality of addressable memory locations 1704, including memory locations 1706 and 1708. These memory locations preferably also are 1024 bits in size. An additional segment of memory also is associated with each of these memory locations. For example, additional memory segment 1760 is associated with memory location 1706, and additional memory segment 1762 is associated with memory location 1708. Status information relating to the data stored in each memory location is stored in the memory segment associated with the memory location. This status information includes, as discussed above, the F/E bit, the SPU ID and the LS address. For example, for memory location 1708, this status information includes F/E bit 1712, SPU ID 1714 and LS address 1716.

Using the status information and the busy bit, the synchronized reading and writing of data from and to the shared DRAM among the SPUs of a PU, or a group of PUs, can be achieved.

FIG. 18 illustrates the initiation of the synchronized writing of data from LS memory location 1732 of SPU 1722 to memory location 1708 of DRAM 1702. Control 1724 of SPU 1722 initiates the synchronized writing of these data. Since memory location 1708 is empty, F/E bit 1712 is set to 0. As a result, the data in LS location 1732 can be written into memory location 1708. If this bit were set to 1 to indicate that memory location 1708 is full and contains current, valid data, on the other hand, control 1722 would receive an error message and be prohibited from writing data into this memory location.

The result of the successful synchronized writing of the data into memory location 1708 is shown in FIG. 19. The written data are stored in memory location 1708, and F/E bit 1712 is set to 1. This setting indicates that memory location 1708 is full and that the data in this memory location are current and valid.

FIG. 20 illustrates the initiation of the synchronized reading of data from memory location 1708 of DRAM 1702 to LS memory location 1750 of local storage 1744. To initiate this reading, the busy bit in memory segment 1752 of LS memory location 1750 is set to 1 to reserve this memory location for these data. The setting of this busy bit to 1 prevents SPU 1740 from storing other data in this memory location.

As shown in FIG. 21, control logic 1742 next issues a synchronize read command for memory location 1708 of DRAM 1702. Since F/E bit 1712 associated with this memory location is set to 1, the data stored in memory location 1708 are considered current and valid. As a result, in preparation for transferring the data from memory location 1708 to LS memory location 1750, F/E bit 1712 is set to 0. This setting is shown in FIG. 22. The setting of this bit to 0 indicates that, following the reading of these data, the data in memory location 1708 will be invalid.

As shown in FIG. 23, the data within memory location 1708 next are read from memory location 1708 to LS memory location 1750. FIG. 24 shows the final state. A copy of the data in memory location 1708 is stored in LS memory location 1750. F/E bit 1712 is set to 0 to indicate that the data in memory location 1708 are invalid. This invalidity is the result of alterations to these data to be made by SPU 1740. The busy bit in memory segment 1752 also is set to 0. This setting indicates that LS memory location 1750 now is available to SPU 1740 for any purpose, i.e., this LS memory location no longer is in a reserved state waiting for the receipt of specific data. LS memory location 1750, therefore, now can be accessed by SPU 1740 for any purpose.

FIGS. 25-31 illustrate the synchronized reading of data from a memory location of DRAM 1702, e.g., memory location 1708, to an LS memory location of an SPU's local storage, e.g., LS memory location 1752 of local storage 1744, when the F/E bit for the memory location of DRAM 1702 is set to 0 to indicate that the data in this memory location are not current or valid. As shown in FIG. 25, to initiate this transfer, the busy bit in memory segment 1752 of LS memory location 1750 is set to 1 to reserve this LS memory location for this transfer of data. As shown in FIG. 26, control logic 1742 next issues a synchronize read command for memory location 1708 of DRAM 1702. Since the F/E bit associated with this memory location, F/E bit 1712, is set to 0, the data stored in memory location 1708 are invalid. As a result, a signal is transmitted to control logic 1742 to block the immediate reading of data from this memory location.

As shown in FIG. 27, the SPU ID 1714 and LS address 1716 for this read command next are written into memory segment 1762. In this case, the SPU ID for SPU 1740 and the LS memory location for LS memory location 1750 are written into memory segment 1762. When the data within memory location 1708 become current, therefore, this SPU ID and LS memory location are used for determining the location to which the current data are to be transmitted.

The data in memory location 1708 become valid and current when an SPU writes data into this memory location. The synchronized writing of data into memory location 1708 from, e.g., memory location 1732 of SPU 1722, is illustrated in FIG. 28. This synchronized writing of these data is permitted because F/E bit 1712 for this memory location is set to 0.

As shown in FIG. 29, following this writing, the data in memory location 1708 become current and valid. SPU ID 1714 and LS address 1716 from memory segment 1762, therefore, immediately are read from memory segment 1762, and this information then is deleted from this segment. F/E bit 1712 also is set to 0 in anticipation of the immediate reading of the data in memory location 1708. As shown in FIG. 30, upon reading SPU ID 1714 and LS address 1716, this information immediately is used for reading the valid data in memory location 1708 to LS memory location 1750 of SPU 1740. The final state is shown in FIG. 31. This figure shows the valid data from memory location 1708 copied to memory location 1750, the busy bit in memory segment 1752 set to 0 and F/E bit 1712 in memory segment 1762 set to 0. The setting of this busy bit to 0 enables LS memory location 1750 now to be accessed by SPU 1740 for any purpose. The setting of this F/E bit to 0 indicates that the data in memory location 1708 no longer are current and valid.

FIG. 32 summarizes the operations described above and the various states of a memory location of the DRAM based upon the states of the F/E bit, the SPU ID and the LS address stored in the memory segment corresponding to the memory location. The memory location can have three states. These three states are an empty state 3280 in which the F/E bit is set to 0 and no information is provided for the SPU ID or the LS address, a full state 3282 in which the F/E bit is set to 1 and no information is provided for the SPU ID or LS address and a blocking state 3284 in which the F/E bit is set to 0 and information is provided for the SPU ID and LS address.

As shown in this figure, in empty state 3280, a synchronized writing operation is permitted and results in a transition to full state 3282. A synchronized reading operation, however, results in a transition to the blocking state 3284 because the data in the memory location, when the memory location is in the empty state, are not current.

In full state 3282, a synchronized reading operation is permitted and results in a transition to empty state 3280. On the other hand, a synchronized writing operation in full state 3282 is prohibited to prevent overwriting of valid data. If such a writing operation is attempted in this state, no state change occurs and an error message is transmitted to the SPU's corresponding control logic.

In blocking state 3284, the synchronized writing of data into the memory location is permitted and results in a transition to empty state 3280. On the other hand, a synchronized reading operation in blocking state 3284 is prohibited to prevent a conflict with the earlier synchronized reading operation which resulted in this state. If a synchronized reading operation is attempted in blocking state 3284, no state change occurs and an error message is transmitted to the SPU's corresponding control logic.

The scheme described above for the synchronized reading and writing of data from and to the shared DRAM also can be used for eliminating the computational resources normally dedicated by a processor for reading data from, and writing data to, external devices. This input/output (I/O) function could be performed by a PU. However, using a modification of this synchronization scheme, an SPU running an appropriate program can perform this function. For example, using this scheme, a PU receiving an interrupt request for the transmission of data from an I/O interface initiated by an external device can delegate the handling of this request to this SPU. The SPU then issues a synchronize write command to the I/O interface. This interface in turn signals the external device that data now can be written into the DRAM. The SPU next issues a synchronize read command to the DRAM to set the DRAM's relevant memory space into a blocking state. The SPU also sets to 1 the busy bits for the memory locations of the SPU's local storage needed to receive the data. In the blocking state, the additional memory segments associated with the DRAM's relevant memory space contain the SPU's ID and the address of the relevant memory locations of the SPU's local storage. The external device next issues a synchronize write command to write the data directly to the DRAM's relevant memory space. Since this memory space is in the blocking state, the data are immediately read out of this space into the memory locations of the SPU's local storage identified in the additional memory segments. The busy bits for these memory locations then are set to 0. When the external device completes writing of the data, the SPU issues a signal to the PU that the transmission is complete.

Using this scheme, therefore, data transfers from external devices can be processed with minimal computational load on the PU. The SPU delegated this function, however, should be able to issue an interrupt request to the PU, and the external device should have direct access to the DRAM.

The DRAM of each PU includes a plurality of “sandboxes.” A sandbox defines an area of the shared DRAM beyond which a particular SPU, or set of SPUs, cannot read or write data. These sandboxes provide security against the corruption of data being processed by one SPU by data being processed by another SPU. These sandboxes also permit the downloading of software cells from network 104 into a particular sandbox without the possibility of the software cell corrupting data throughout the DRAM. In the present invention, the sandboxes are implemented in the hardware of the DRAMs and DMACs. By implementing these sandboxes in this hardware rather than in software, advantages in speed and security are obtained.

The PU of a PU controls the sandboxes assigned to the SPUs. Since the PU normally operates only trusted programs, such as an operating system, this scheme does not jeopardize security. In accordance with this scheme, the PU builds and maintains a key control table. This key control table is illustrated in FIG. 33. As shown in this figure, each entry in key control table 3302 contains an identification (ID) 3304 for an SPU, an SPU key 3306 for that SPU and a key mask 3308. The use of this key mask is explained below. Key control table 3302 preferably is stored in a relatively fast memory, such as a static random access memory (SRAM), and is associated with the DMAC. The entries in key control table 3302 are controlled by the PU. When an SPU requests the writing of data to, or the reading of data from, a particular storage location of the DRAM, the DMAC evaluates the SPU key 3306 assigned to that SPU in key control table 3302 against a memory access key associated with that storage location.

As shown in FIG. 34, a dedicated memory segment 3410 is assigned to each addressable storage location 3406 of a DRAM 3402. A memory access key 3412 for the storage location is stored in this dedicated memory segment. As discussed above, a further additional dedicated memory segment 3408, also associated with each addressable storage location 3406, stores synchronization information for writing data to, and reading data from, the storage-location.

In operation, an SPU issues a DMA command to the DMAC. This command includes the address of a storage location 3406 of DRAM 3402. Before executing this command, the DMAC looks up the requesting SPU's key 3306 in key control table 3302 using the SPU's ID 3304. The DMAC then compares the SPU key 3306 of the requesting SPU to the memory access key 3412 stored in the dedicated memory segment 3410 associated with the storage location of the DRAM to which the SPU seeks access. If the two keys do not match, the DMA command is not executed. On the other hand, if the two keys match, the DMA command proceeds and the requested memory access is executed.

An alternative embodiment is illustrated in FIG. 35. In this embodiment, the PU also maintains a memory access control table 3502. Memory access control table 3502 contains an entry for each sandbox within the DRAM. In the particular example of FIG. 35, the DRAM contains 64 sandboxes. Each entry in memory access control table 3502 contains an identification (ID) 3504 for a sandbox, a base memory address 3506, a sandbox size 3508, a memory access key 3510 and an access key mask 3512. Base memory address 3506 provides the address in the DRAM which starts a particular memory sandbox. Sandbox size 3508 provides the size of the sandbox and, therefore, the endpoint of the particular sandbox.

FIG. 36 is a flow diagram of the steps for executing a DMA command using key control table 3302 and memory access control table 3502. In step 3602, an SPU issues a DMA command to the DMAC for access to a particular memory location or locations within a sandbox. This command includes a sandbox ID 3504 identifying the particular sandbox for which access is requested. In step 3604, the DMAC looks up the requesting SPU's key 3306 in key control table 3302 using the SPU's ID 3304. In step 3606, the DMAC uses the sandbox ID 3504 in the command to look up in memory access control table 3502 the memory access key 3510 associated with that sandbox. In step 3608, the DMAC compares the SPU key 3306 assigned to the requesting SPU to the access key 3510 associated with the sandbox. In step 3610, a determination is made of whether the two keys match. If the two keys do not match, the process moves to step 3612 where the DMA command does not proceed and an error message is sent to either the requesting SPU, the PU or both. On the other hand, if at step 3610 the two keys are found to match, the process proceeds to step 3614 where the DMAC executes the DMA command.

The key masks for the SPU keys and the memory access keys provide greater flexibility to this system. A key mask for a key converts a masked bit into a wildcard. For example, if the key mask 3308 associated with an SPU key 3306 has its last two bits set to “mask,” designated by, e.g., setting these bits in key mask 3308 to 1, the SPU key can be either a 1 or a 0 and still match the memory access key. For example, the SPU key might be 1010. This SPU key normally allows access only to a sandbox having an access key of 1010. If the SPU key mask for this SPU key is set to 0001, however, then this SPU key can be used to gain access to sandboxes having an access key of either 1010 or 1011. Similarly, an access key 1010 with a mask set to 0001 can be accessed by an SPU with an SPU key of either 1010 or 1011. Since both the SPU key mask and the memory key mask can be used simultaneously, numerous variations of accessibility by the SPUs to the sandboxes can be established.

The present invention also provides a new programming model for the processors of system 101. This programming model employs software cells 102. These cells can be transmitted to any processor on network 104 for processing. This new programming model also utilizes the unique modular architecture of system 101 and the processors of system 101.

Software cells are processed directly by the SPUs from the SPU's local storage. The SPUs do not directly operate on any data or programs in the DRAM. Data and programs in the DRAM are read into the SPU's local storage before the SPU processes these data and programs. The SPU's local storage, therefore, includes a program counter, stack and other software elements for executing these programs. The PU controls the SPUs by issuing direct memory access (DMA) commands to the DMAC.

The structure of software cells 102 is illustrated in FIG. 37. As shown in this figure, a software cell, e.g., software cell 3702, contains routing information section 3704 and body 3706. The information contained in routing information section 3704 is dependent upon the protocol of network 104. Routing information section 3704 contains header 3708, destination ID 3710, source ID 3712 and reply ID 3714. The destination ID includes a network address. Under the TCP/IP protocol, e.g., the network address is an Internet protocol (IP).address. Destination ID 3710 further includes the identity of the PU and SPU to which the cell should be transmitted for processing. Source ID 3712 contains a network address and identifies the PU and SPU from which the cell originated to enable the destination PU and SPU to obtain additional information regarding the cell if necessary. Reply ID 3714 contains a network address and identifies the PU and SPU to which queries regarding the cell, and the result of processing of the cell, should be directed.

Cell body 3706 contains information independent of the network's protocol. The exploded portion of FIG. 37 shows the details of cell body 3706. Header 3720 of cell body 3706 identifies the start of the cell body. Cell interface 3722 contains information necessary for the cell's utilization. This information includes global unique ID 3724, required SPUs 3726, sandbox size 3728 and previous cell ID 3730.

Global unique ID 3724 uniquely identifies software cell 3702 throughout network 104. Global unique ID 3724 is generated on the basis of source ID 3712, e.g. the unique identification of a PU or SPU within source ID 3712, and the time and date of generation or transmission of software cell 3702. Required SPUs 3726 provides the minimum number of SPUs required to execute the cell. Sandbox size 3728 provides the amount of protected memory in the required SPUs' associated DRAM necessary to execute the cell. Previous cell ID 3730 provides the identity of a previous cell in a group of cells requiring sequential execution, e.g., streaming data.

Implementation section 3732 contains the cell's core information. This information includes DMA command list 3734, programs 3736 and data 3738. Programs 3736 contain the programs to be run by the SPUs (called “spulets”), e.g., SPU programs 3760 and 3762, and data 3738 contain the data to be processed with these programs. DMA command list 3734 contains a series of DMA commands needed to start the programs. These DMA commands include DMA commands 3740, 3750, 3755 and 3758. The PU issues these DMA commands to the DMAC.

DMA command 3740 includes VID 3742. VID 3742 is the virtual ID of an SPU which is mapped to a physical ID when the DMA commands are issued. DMA command 3740 also includes load command 3744 and address 3746. Load command 3744 directs the SPU to read particular information from the DRAM into local storage. Address 3746 provides the virtual address in the DRAM containing this information. The information can be, e.g., programs from programs section 3736, data from data section 3738 or other data. Finally, DMA command 3740 includes local storage address 3748. This address identifies the address in local storage where the information should be loaded. DMA commands 3750 contain similar information. Other DMA commands are also possible.

DMA command list 3734 also includes a series of kick commands, e.g., kick commands 3755 and 3758. Kick commands are commands issued by a PU to an SPU to initiate the processing of a cell. DMA kick command 3755 includes virtual SPU ID 3752, kick command 3754 and program counter 3756. Virtual SPU ID 3752 identifies the SPU to be kicked, kick command 3754 provides the relevant kick command and program counter 3756 provides the address for the program counter for executing the program. DMA kick command 3758 provides similar information for the same SPU or another SPU.

As noted, the PUs treat the SPUs as independent processors, not co-processors. To control processing by the SPUs, therefore, the PU uses commands analogous to remote procedure calls. These commands are designated “SPU Remote Procedure Calls” (SRPCs). A PU implements an SRPC by issuing a series of DMA commands to the DMAC. The DMAC loads the SPU program and its associated stack frame into the local storage of an SPU. The PU then issues an initial kick to the SPU to execute the SPU Program.

FIG. 38 illustrates the steps of an SRPC for executing an spulet. The steps performed by the PU in initiating processing of the spulet by a designated SPU are shown in the first portion 3802 of FIG. 38, and the steps performed by the designated SPU in processing the spulet are shown in the second portion 3804 of FIG. 38.

In step 3810, the PU evaluates the spulet and then designates an SPU for processing the spulet. In step 3812, the PU allocates space in the DRAM for executing the spulet by issuing a DMA command to the DMAC to set memory access keys for the necessary sandbox or sandboxes. In step 3814, the PU enables an interrupt request for the designated SPU to signal completion of the spulet. In step 3818, the PU issues a DMA command to the DMAC to load the spulet from the DRAM to the local storage of the SPU. In step 3820, the DMA command is executed, and the spulet is read from the DRAM to the SPU's local storage. In step 3822, the PU issues a DMA command to the DMAC to load the stack frame associated with the spulet from the DRAM to the SPU's local storage. In step 3823, the DMA command is executed, and the stack frame is read from the DRAM to the SPU's local storage. In step 3824, the PU issues a DMA command for the DMAC to assign a key to the SPU to allow the SPU to read and write data from and to the hardware sandbox or sandboxes designated in step 3812. In step 3826, the DMAC updates the key control table (KTAB) with the key assigned to the SPU. In step 3828, the PU issues a DMA command “kick” to the SPU to start processing of the program. Other DMA commands may be issued by the PU in the execution of a particular SRPC depending upon the particular spulet.

As indicated above, second portion 3804 of FIG. 38 illustrates the steps performed by the SPU in executing the spulet. In step 3830, the SPU begins to execute the spulet in response to the kick command issued at step 3828. In step 3832, the SPU, at the direction of the spulet, evaluates the spulet's associated stack frame. In step 3834, the SPU issues multiple DMA commands to the DMAC to load data designated as needed by the stack frame from the DRAM to the SPU's local storage. In step 3836, these DMA commands are executed, and the data are read from the DRAM to the SPU's local storage. In step 3838, the SPU executes the spulet and generates a result. In step 3840, the SPU issues a DMA command to the DMAC to store the result in the DRAM. In step 3842, the DMA command is executed and the result of the spulet is written from the SPU's local storage to the DRAM. In step 3844, the SPU issues an interrupt request to the PU to signal that the SRPC has been completed.

The ability of SPUs to perform tasks independently under the direction of a PU enables a PU to dedicate a group of SPUs, and the memory resources associated with a group of SPUs, to performing extended tasks. For example, a PU can dedicate one or more SPUs, and a group of memory sandboxes associated with these one or more SPUs, to receiving data transmitted over network 104 over an extended period and to directing the data received during this period to one or more other SPUs and their associated memory sandboxes for further processing. This ability is particularly advantageous to processing streaming data transmitted over network 104, e.g., streaming MPEG or streaming ATRAC audio or video data. A PU can dedicate one or more SPUs and their associated memory sandboxes to receiving these data and one or more other SPUs and their associated memory sandboxes to decompressing and further processing these data. In other words, the PU can establish a dedicated pipeline relationship among a group of SPUs and their associated memory sandboxes for processing such data.

In order for such processing to be performed efficiently, however, the pipeline's dedicated SPUs and memory sandboxes should remain dedicated to the pipeline during periods in which processing of spulets comprising the data stream does not occur. In other words, the dedicated SPUs and their associated sandboxes should be placed in a reserved state during these periods. The reservation of an SPU and its associated memory sandbox or sandboxes upon completion of processing of an spulet is called a “resident termination.” A resident termination occurs in response to an instruction from a PU.

FIGS. 39, 40A and 40B illustrate the establishment of a dedicated pipeline structure comprising a group of SPUs and their associated sandboxes for the processing of streaming data, e.g., streaming MPEG data. As shown in FIG. 39, the components of this pipeline structure include PE 3902 and DRAM 3918. PE 3902 includes PU 3904, DMAC 3906 and a plurality of SPUs, including SPU 3908, SPU 3910 and SPU 3912. Communications among PU 3904, DMAC 3906 and these SPUs occur through PE bus 3914. Wide bandwidth bus 3916 connects DMAC 3906 to DRAM 3918. DRAM 3918 includes a plurality of sandboxes, e.g., sandbox 3920, sandbox 3922, sandbox 3924 and sandbox 3926.

FIG. 40A illustrates the steps for establishing the dedicated pipeline. In step 4010, PU 3904 assigns SPU 3908 to process a network spulet. A network spulet comprises a program for processing the network protocol of network 104. In this case, this protocol is the Transmission Control Protocol/Internet Protocol (TCP/IP). TCP/IP data packets conforming to this protocol are transmitted over network 104. Upon receipt, SPU 3908 processes these packets and assembles the data in the packets into software cells 102. In step 4012, PU 3904 instructs SPU 3908 to perform resident terminations upon the completion of the processing of the network spulet. In step 4014, PU 3904 assigns PUs 3910 and 3912 to process MPEG spulets. In step 4015, PU 3904 instructs SPUs 3910 and 3912 also to perform resident terminations upon the completion of the processing of the MPEG spulets. In step 4016, PU 3904 designates sandbox 3920 as a source sandbox for access by SPU 3908 and SPU 3910. In step 4018, PU 3904 designates sandbox 3922 as a destination sandbox for access by SPU 3910. In step 4020, PU 3904 designates sandbox 3924 as a source sandbox for access by SPU 3908 and SPU 3912. In step 4022, PU 3904 designates sandbox 3926 as a destination sandbox for access by SPU 3912. In step 4024, SPU 3910 and SPU 3912 send synchronize read commands to blocks of memory within, respectively, source sandbox 3920 and source sandbox 3924 to set these blocks of memory into the blocking state. The process finally moves to step 4028 where establishment of the dedicated pipeline is complete and the resources dedicated to the pipeline are reserved. SPUs 3908, 3910 and 3912 and their associated sandboxes 3920, 3922, 3924 and 3926, therefore, enter the reserved state.

FIG. 40B illustrates the steps for processing streaming MPEG data by this dedicated pipeline. In step 4030, SPU 3908, which processes the network spulet, receives in its local storage TCP/IP data packets from network 104. In step 4032, SPU 3908 processes these TCP/IP data packets and assembles the data within these packets into software cells 102. In step 4034, SPU 3908 examines header 3720 (FIG. 37) of the software cells to determine whether the cells contain MPEG data. If a cell does not contain MPEG data, then, in step 4036, SPU 3908 transmits the cell to a general purpose sandbox designated within DRAM 3918 for processing other data by other SPUs not included within the dedicated pipeline. SPU 3908 also notifies PU 3904 of this transmission.

On the other hand, if a software cell contains MPEG data, then, in step 4038, SPU 3908 examines previous cell ID 3730 (FIG. 37) of the cell to identify the MPEG data stream to which the cell belongs. In step 4040, SPU 3908 chooses an SPU of the dedicated pipeline for processing of the cell. In this case, SPU 3908 chooses SPU 3910 to process these data. This choice is based upon previous cell ID 3730 and load balancing factors. For example, if previous cell ID 3730 indicates that the previous software cell of the MPEG data stream to which the software cell belongs was sent to SPU 3910 for processing, then the present software cell normally also will be sent to SPU 3910 for processing. In step 4042, SPU 3908 issues a synchronize write command to write the MPEG data to sandbox 3920. Since this sandbox previously was set to the blocking state, the MPEG data, in step 4044, automatically is read from sandbox 3920 to the local storage of SPU 3910. In step 4046, SPU 3910 processes the MPEG data in its local storage to generate video data. In step 4048, SPU 3910 writes the video data to sandbox 3922. In step 4050, SPU 3910 issues a synchronize read command to sandbox 3920 to prepare this sandbox to receive additional MPEG data. In step 4052, SPU 3910 processes a resident termination. This processing causes this SPU to enter the reserved state during which the SPU waits to process additional MPEG data in the MPEG data stream.

Other dedicated structures can be established among a group of SPUs and their associated sandboxes for processing other types of data. For example, as shown in FIG. 41, a dedicated group of SPUs, e.g., SPUs 4102, 4108 and 4114, can be established for performing geometric transformations upon three dimensional objects to generate two dimensional display lists. These two dimensional display lists can be further processed (rendered) by other SPUs to generate pixel data. To perform this processing, sandboxes are dedicated to SPUs 4102, 4108 and 4114 for storing the three dimensional objects and the display lists resulting from the processing of these objects. For example, source sandboxes 4104, 4110 and 4116 are dedicated to storing the three dimensional objects processed by, respectively, SPU 4102, SPU 4108 and SPU 4114. In a similar manner, destination sandboxes 4106, 4112 and 4118 are dedicated to storing the display lists resulting from the processing of these three dimensional objects by, respectively, SPU 4102, SPU 4108 and SPU 4114.

Coordinating SPU 4120 is dedicated to receiving in its local storage the display lists from destination sandboxes 4106, 4112 and 4118. SPU 4120 arbitrates among these display lists and sends them to other SPUs for the rendering of pixel data.

The processors of system 101 also employ an absolute timer. The absolute timer provides a clock signal to the SPUs and other elements of a PU which is both independent of, and faster than, the clock signal driving these elements. The use of this absolute timer is illustrated in FIG. 42.

As shown in this figure, the absolute timer establishes a time budget for the performance of tasks by the SPUs. This time budget provides a time for completing these tasks which is longer than that necessary for the SPUs' processing of the tasks. As a result, for each task, there is, within the time budget, a busy period and a standby period. All spulets are written for processing on the basis of this time budget regardless of the SPUs' actual processing time or speed.

For example, for a particular SPU of a PU, a particular task may be performed during busy period 4202 of time budget 4204. Since busy period 4202 is less than time budget 4204, a standby period 4206 occurs during the time budget. During this standby period, the SPU goes into a sleep mode during which less power is consumed by the SPU.

The results of processing a task are not expected by other SPUs, or other elements of a PU, until a time budget 4204 expires. Using the time budget established by the absolute timer, therefore, the results of the SPUs' processing always are coordinated regardless of the SPUs' actual processing speeds.

In the future, the speed of processing by the SPUs will become faster. The time budget established by the absolute timer, however, will remain the same. For example, as shown in FIG. 42, an SPU in the future will execute a task in a shorter period and, therefore, will have a longer standby period. Busy period 4208, therefore, is shorter than busy period 4202, and standby period 4210 is longer than standby period 4206. However, since programs are written for processing on the basis of the same time budget established by the absolute timer, coordination of the results of processing among the SPUs is maintained. As a result, faster SPUs can process programs written for slower SPUs without causing conflicts in the times at which the results of this processing are expected.

In lieu of an absolute timer to establish coordination among the SPUs, the PU, or one or more designated SPUs, can analyze the particular instructions or microcode being executed by an SPU in processing an spulet for problems in the coordination of the SPUs' parallel processing created by enhanced or different operating speeds. “No operation” (“NOOP”) instructions can be inserted into the instructions and executed by some of the SPUs to maintain the proper sequential completion of processing by the SPUs expected by the spulet. By inserting these NOOPs into the instructions, the correct timing for the SPUs' execution of all instructions can be maintained.

FIG. 43 is a flowchart showing the steps taken to compile a given source code into object files adapted to execute in a heterogeneous processor environment. Processing commences at 4300 whereupon, at step 4305, a request is received from a programmer or automated process to compile source code. The request may include compiler options 4310. The programmer or automated process can set compiler options to determine whether the source code is compiled into object code adapted to be executed on an SPU processor, a PU processor, or both.

At step 4315, source code 4320 is read. A determination is made, based on the compiler options, as to whether source code 4320 is to be compiled for multiple processors (decision 4325). If the source code is being compiled for multiple processors, decision 4325 branches to “yes” branch 4328 to analyze the code and create two object files—one adapted to run on one or more SPU processors and another object file adapted to run on one or more PU processors.

The data locality is analyzed in step 4330 and a value is assigned based on the analysis. SPU processors are generally better at handling streaming data, while PU processors are generally better at handling scattered data (scattered data being where subsequent blocks of data for processing are found in discontiguous memory locations while in streaming data, the data being processed is generally contiguous. In one embodiment, the programmer inserts compiler flags or other indicators in the source code indicating that various portions of the source code are processing streaming or scattered data. If the data processing of the source code is found to be more streaming in nature a higher value is assigned than if the data processing is found to be scattered.

The computational needs of the source program are analyzed at step 4335 and a value is assigned based on the analysis. SPU processors are generally better at handling more computationally intensive tasks, especially mathematical tasks, than the PU processors. If the computational intensity of the program is found to be high, then a higher value is assigned. Likewise, if the computational intensity is low, a lower value is assigned.

At step 4340, the data parallelism of the data being processed by the source code is analyzed and a value is assigned based on the analysis. SPU processors are generally better at processing parallel sets of data as, in one embodiment, the SPU processors are SIMD (Single Instruction Multiple Data) processors able to perform a single instruction against more than one set of data. Parallel streams of data can be read into the SPU processors memory and processed simultaneously using the same instructions. However, in a non-SIMD processor, such as a traditional PU processor, each stream of data is processed separately with the same instructions used multiple times to process the multiple streams of data. If the data parallelism is found to be high, then a higher value is assigned. Likewise, if the data parallelism is found to be low, then a lower value is assigned.

At step 4345, the source code is compiled into PU object 4350 that is adapted to be loaded and executed on the PU (i.e., PU machine instructions suitable for the PU environment). The compiled object includes a header area that contains the values from the analyses performed in steps 4330-4340. These values will subsequently be used by when the program is invoked to determine whether to load the PU object or the SPU object.

At step 4355, the source code is compiled into SPU object 4360 that is adapted to be loaded and executed on the SPU (i.e., SPU machine instructions suitable for the SPU environment). The compiled object includes a header area that contains the values from the analyses performed in steps 4330-4340. These values will subsequently be used by when the program is invoked to determine whether to load the PU object or the SPU object. Compilation processing thereafter ends at 4395.

Returning to decision 4325, if the software code is not being compiled for multiple processors, decision 4325 branches to “no” branch 4368 whereupon a determination is made as to whether the source code is being compiled for the PU environment or the SPU environment (decision 4370). If the source code is only being compiled for the PU environment, decision 4370 branches to “PU” branch 4372 whereupon, at step 4375, the code is compiled into PU object 4380 suitable for executing in the PU environment. Similarly, if the source code is being compiled for the SPU environment, decision 4370 branches to “SPU” branch 4372 whereupon, at step 4385, the code is compiled into SPU object 4390 suitable for executing in the SPU environment. Compilation processing thereafter ends at 4395.

FIG. 44 is a flowchart showing steps taken by a loader in the heterogeneous processor environment selecting in selecting one of the heterogeneous processor types to execute an object file. Processing commences at 4400 whereupon, at step 4402, a load request is received to load and execute an executable program (i.e., an object file).

At step 4405, object file(s) 4410 and data 4415 matching the request are retrieved. The object file(s) are retrieved from a nonvolatile storage device, while the data is either retrieved from a nonvolatile storage device or from a memory location if the data was generated from another process.

A determination is made as to whether there is a single object file (i.e., the program is only suitable for one of the processing environments) or more than one object file matching the request (decision 4420). If there are more than one object file matching the request, decision 4420 branches to “no” branch 4422 whereupon the processor to be used for executing one of the objects is identified (predefined process 4425, see FIG. 45 and corresponding text for processing details). On the other hand, if there is only one processing environment, decision 4420 branches to “yes” branch 4428 bypassing predefined process 4425.

A determination is made as to whether to execute on the PU or SPU processing environment based upon whether there is only a single object and, if multiple objects are available, which environment is preferred based upon program characteristics and current processor availability (decision 4430). If the PU processor was selected, decision 4430 branches to “PU” branch 4432 whereupon, at step 4435, the PU object code is loaded into common (shared) memory 4470. If the data being processed does not yet reside in memory 4470, it is also loaded (i.e., retrieved from nonvolatile storage) into memory 4470. At step 4440, an output buffer is initialized. The output buffer is used to store data resulting from the execution of the PU object. It can be initialized by the loader or can be allocated later through instructions included in the PU object. At step 4445, the PU object is scheduled for execution on one of the PU processors by writing the PU object's identifier into run queue 4450. The PU's scheduler (4455) dispatches tasks, including the newly scheduled PU object, for execution by PU processor 4460. Load processing thereafter ends at 4495.

Returning to decision 4430, if the SPU processor environment was selected, decision 4430 branches to “SPU” branch 4462 whereupon, at step 4465, the SPU object is loaded into common (shared) memory 4470. If the data being processed does not yet reside in memory 4470, it is also loaded into memory 4470. At step 4468, an output buffer is initialized in memory 4470. The output buffer is the location to which the SPU will write, via a DMA command, data resulting from the SPU's execution of the SPU object. At step 4475, an instruction block is created and written to common memory 4470. The instruction block details the address of the SPU object file that was loaded into common memory 4470, the address of the input buffer located in common memory that the SPU will process, the address of the output buffer, also stored in common memory 4470, to which the SPU will write data resulting from the SPU's processing of the SPU object file. The instruction block can also include other parameters that are being passed to the SPU object, such as write-back addresses and parameters particular to the object being executed. At step 4480, the address of the instruction block is written to a mailbox (4485) corresponding to one of the SPUs (for a detailed description of the SPU's execution of the object file, see FIG. 46). Load processing thereafter ends at 4495.

FIG. 45 is a flowchart showing steps taken by the loader in the heterogeneous processor environment identifying a preferred processor for a given task. Processing commences at 4500 when this routine was called from predefined process 4425 shown in FIG. 44. Returning to FIG. 45, upon commencing, at step 4505, processor availability is retrieved. If availability of the PU processor (or processors) is greater (better) than SPU availability, then a low value is assigned. Likewise, if availability of the SPU processors is greater (better) than availability of the PU processor (or processors), then a high value is assigned. If both processor types are equally available, then a middle (neutral) value is assigned.

A determination is made, based on the analysis of processor availability in step 4505, as to whether one of the processor types is currently unavailable (decision 4510). If one of the processor types (PU or SPU) is currently unavailable, decision 4510 branches to “yes” branch 4570 whereupon a determination is made as to whether to wait for the unavailable processor type to become available (decision 4575). If it is decided to wait for the unavailable processor type to become available, decision 4575 branches to “yes” branch 4580 whereupon, at step 4580, processing waits until the unavailable processor type is available and, when the processor type is available, processing branches to step 4520, described below. On the other hand, if it is decided not to wait for the unavailable processor type to become available, decision 4575 branches to “no” branch 4585 whereupon, at step 4590, the task is assigned to whichever processor type is available. Processing then returns at 4595 (see FIG. 44).

Returning to decision 4510, if both processor types are currently available, decision 4510 branches to “no” branch 4515 whereupon, at step 4520-4530, characteristics of the object being loaded are retrieved from a header area associated with the object. Data in the header area was written to the header area during compilation (see FIG. 43 for compilation details).

At step 4520, the computational intensity value is retrieved from the object's header area. A high computational intensity value indicates that the task is generally more suited to being run on an SPU processor, whereas a lower computational intensity value indicates that the computations can be performed well on the PU processor.

At step 4525, the data locality value is retrieved from the object's header area. A high data locality value indicates that the data is localized (i.e., more streamed than scattered). Streamed data is generally processed more efficiently by the SPU processor, while scattered data is generally processed more efficiently by the PU processor.

At step 4530, the data parallelism value is retrieved from the object's header area. A high data parallelism value indicates that the data can be processed by the SIMD (Single-Instruction-Multiple-Data) operations available on the SPU. A low data parallelism value indicates that the data is not highly parallelized and will not be able to utilize the SIMD aspects of the SPU processor, so the PU processor can be utilized instead of the SPU processor.

At step 4535, the size of the data being processed is identified by checking the size of the input buffer or data file that will be processed by the object. SPUs are generally better than the PU processor at processing large quantities of data quickly. Therefore, a larger input data file being processed is given a higher data size score than smaller input files.

At step 4538, an overall score is computed by combining the processor availability score, the computational intensity score, the data locality score, the data parallelism score, and the data size score. In one embodiment the scores are simply added together. For example, each score may be worth a maximum of ten so, by combining the five scores, a maximum value of 50 is available as an overall score. In other embodiments, the scores are weighted based on the particular function of the computer system or after tuning the system with regards to common tasks that are performed. In any event, an overall score is achieved that is used to determine whether to assign the task to the PU or the SPU.

A determination is made, based on the overall score, as to whether the overall score is high-or low (decision 4540). Using a simple model, if the maximum possible overall score is 50, then a score greater than 25 could be considered high. The “high” value can also be tuned to assign more, or less, tasks to the SPU. For example, after tuning, a “high” score may be set at 20 to assign more tasks to the SPU or may be set at 30 to assign more tasks to the PU. If the overall score is high, decision 4540 branches to “yes” branch 4545 whereupon the task is assigned to be performed by an SPU, at step 4550, and at step 4555 one or more SPUs are identified based upon the SPUs' current availability. On the other hand, if the overall score is not high, decision 4540 branches to “no” branch 4560 whereupon the task is assigned to a PU (see FIG. 44 for details on the loader adding the task to the PU's run queue, and see FIGS. 44 and 46 for details on the loader instructing a SPU to perform the task (FIG. 44) and the SPU retrieving and performing the task (FIG. 46).

FIG. 46 is a flowchart showing steps taken by an SPU processor in executing an object file scheduled to it by the loader. FIG. 44 showed the steps of the loader creating instruction blocks 4635 (see instruction block stored to common memory 4470 in FIG. 44) and notifying the SPU by signaling SPU mailbox 4615 (see 4485 in FIG. 44). Processing commences at 4600 whereupon, at step 4610, the SPU checks mailbox 4615. A determination is made as to whether the mailbox is empty or has entries to process (decision 4620). If the mailbox is empty, decision 4620 branches to “yes” branch 4622 which continues to check the mailbox. In one embodiment, the SPU is interrupted when an entry arrives in the mailbox and when there are no entries in the mailbox (and the SPU is not busy processing a task), the SPU enters a low power state while it waits for an entry to arrive.

When an entry arrives, decision 4620 branches to “no” branch 4628 whereupon, at step 4630, the address in the mailbox is retrieved and used to retrieve instruction block 4635 stored in the common (shared) memory. The SPU retrieves the instruction block using a DMA command. In one embodiment, a DMA controller is provided for each SPU and PU to perform DMA commands and retrieve and store data to the common, shared memory. The instruction block includes a code address for the code that the SPU is to execute, an input buffer address for the input buffer of the data that is to be processed, an output buffer address for the output buffer where data resulting from the SPU's execution of the code is to be stored, and an optional signal instruction, such as a write-back address, that the SPU should use to indicate when it is finished processing the data. In addition, other parameters that might be used by the code can be included in the instruction block and provided as input to the code once it has been loaded by the SPU.

At step 4640, the code referenced in the instruction block is moved, using a DMA command, from shared memory location 4680 in shared (common) memory 4675 to the SPU's local memory (4695). In one embodiment, the SPU local storage is 128K bytes in length.

At step 4650, the code that has been loaded is execute. Prior to and during execution, blocks from input buffer 4685 located in shared (common) memory 4675 are written to the SPU's local memory 4695 using DMA commands. The amount of data that can be read into the SPU's local memory depends on the size of the code being executed and the amount of local memory that is reserved for storing result data. During execution, blocks from SPU local memory 4695 that contain results from executing the code are written to output buffer 4690 located in shared (common) memory 4675 using DMA commands. Again, the amount of SPU local memory that can be used to store result data before the data needs to be written back to the shared memory depends upon the size of the code being executed and the amount of space reserved to store input data.

At step 4660, execution of the code ends and the last results from processing the code have been written from SPU local memory back to the shared memory using a DMA command. The SPU, at step 4670, notifies the scheduler (loader) that it is finished executing the code. At this point, the SPU loops back to check its mailbox to determine whether there are additional requests to process and, if the mailbox is empty, wait for new requests to arrive.

FIG. 47 is a block diagram illustrating a processing element having a main processor and a plurality of secondary processors sharing a system memory. Processor Element (PE) 4705 includes processing unit (PU) 4710, which, in one embodiment, acts as the main processor and runs an operating system. Processing unit 4710 may be, for example, a Power PC core executing a Linux operating system. PE 4705 also includes a plurality of synergistic processing complex's (SPCs) such as SPCs 4745, 4765, and 4785. The SPCs include synergistic processing units (SPUs) that act as secondary processing units to PU 4710, a memory storage unit, and local storage. For example, SPC 4745 includes SPU 4760, MMU 4755, and local storage 4759; SPC 4765 includes SPU 4770, MMU 4775, and local storage 4779; and SPC 4785 includes SPU 4790, MMU 4795, and local storage 4799.

Each SPC may be configured to perform a different task, and accordingly, in one embodiment, each SPC may be accessed using different instruction sets. If PE 4705 is being used in a wireless communications system, for example, each SPC may be responsible for separate processing tasks, such as modulation, chip rate processing, encoding, network interfacing, etc. In another embodiment, the SPCs may have identical instruction sets and may be used in parallel with each other to perform operations benefiting from parallel processing.

PE 4705 may also include level 2 cache, such as L2 cache 4715, for the use of PU 4710. In addition, PE 4705 includes system memory 4720, which is shared between PU 4710 and the SPUs. System memory 4720 may store, for example, an image of the running operating system (which may include the kernel), device drivers, I/O configuration, etc., executing applications, as well as other data. System memory 4720 includes the local storage units of one or more of the SPCs, which are mapped to a region of system memory 4720. For example, local storage 4759 may be mapped to mapped region 4735, local storage 4779 may be mapped to mapped region 4740, and local storage 4799 may be mapped to mapped region 4742. PU 4710 and the SPCs communicate with each other and system memory 4720 through bus 4717 that is configured to pass data between these devices.

The MMUs are responsible for transferring data between an SPU's local store and the system memory. In one embodiment, an MMU includes a direct memory access (DMA) controller configured to perform this function. PU 4710 may program the MMUs to control which memory regions are available to each of the MMUs. By changing the mapping available to each of the MMUs, the PU may control which SPU has access to which region of system memory 4720. In this manner, the PU may, for example, designate regions of the system memory as private for the exclusive use of a particular SPU. In one embodiment, the SPUs' local stores may be accessed by PU 4710 as well as by the other SPUs using the memory map. In one embodiment, PU 4710 manages the memory map for the common system memory 4720 for all the SPUs. The memory map table may include PU 4710's L2 Cache 4715, system memory 4720, as well as the SPUs' shared local stores.

In one embodiment, the SPUs process data under the control of PU 4710. The SPUs may be, for example, digital signal processing cores, microprocessor cores, micro controller cores, etc., or a combination of the above cores. Each one of the local stores is a storage area associated with a particular SPU. In one embodiment, each SPU can configure its local store as a private storage area, a shared storage area, or an SPU may configure its local store as a partly private and partly shared storage.

For example, if an SPU requires a substantial amount of local memory, the SPU may allocate 100% of its local store to private memory accessible only by that SPU. If, on the other hand, an SPU requires a minimal amount of local memory, the SPU may allocate 10% of its local store to private memory and the remaining 90% to shared memory. The shared memory is accessible by PU 4710 and by the other SPUs. An SPU may reserve part of its local store in order for the SPU to have fast, guaranteed memory access when performing tasks that require such fast access. The SPU may also reserve some of its local store as private when processing sensitive data, as is the case, for example, when the SPU is performing encryption/decryption.

Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims.

One of the preferred implementations of the invention is an application, namely, a set of instructions (program code) in a code module which may, for example, be resident in the random access memory of the computer. Until required by the computer, the set of instructions may be stored in another computer memory, for example, on a hard disk drive, or in removable storage such as an optical disk (for eventual use in a CD ROM) or floppy disk (for eventual use in a floppy disk drive), or downloaded via the Internet or other computer network. Thus, the present invention may be implemented as a computer program product for use in a computer. In addition, although the various methods described are conveniently implemented in a general purpose computer selectively activated or reconfigured by software, one of ordinary skill in the art would also recognize that such methods may be carried out in hardware, in firmware, or in more specialized apparatus constructed to perform the required method steps.

While particular embodiments of the present invention have been shown and described, it will be obvious to those skilled in the art that, based upon the teachings herein, changes and modifications may be made without departing from this invention and its broader aspects and, therefore, the appended claims are to encompass within their scope all such changes and modifications as are within the true spirit and scope of this invention. Furthermore, it is to be understood that the invention is solely defined by the appended claims. It will be understood by those with skill in the art that if a specific number of an introduced claim element is intended, such intent will be explicitly recited in the claim, and in the absence of such recitation no such limitation is present. For a non-limiting example, as an aid to understanding, the following appended claims contain usage of the introductory phrases “at least one” and “one or more” to introduce claim elements. However, the use of such phrases should not be construed to imply that the introduction of a claim element by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim element to inventions containing only one such element, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an”; the same holds true for the use in the claims of definite articles. 

1. A computer-implemented method for loading objects in a heterogeneous multiprocessor computer system, said method comprising: identifying a processor to execute a software task, the identification based upon characteristics of the software task and computing resource availability; loading software code corresponding to the identified processor into a shared memory, wherein the shared memory is shared by a plurality of dislike processors that includes the identified processor; and executing the loaded code by the identified processor.
 2. The method as described in claim 1 further comprising: prior to the identifying, compiling a source program into at least two object files, each adapted to be executed on a different processor selected from the plurality of dislike processors, wherein the software code that is loaded and executed is one of the object files.
 3. The method as described in claim 2 further comprising: analyzing the source program for program characteristics; and storing the program characteristics.
 4. The method as described in claim 3 wherein at least one of the program characteristics is selected from the group consisting of data locality, computational intensity, and data parallelism.
 5. The method as described in claim 3 wherein identifying the processor further comprises: retrieving the program characteristics; retrieving current system characteristics, wherein the current system characteristics includes processor load characteristics for the plurality of dislike processors; and combining the program characteristics and the current system characteristics to determine which of the dislike processors to assign the software task.
 6. The method as described in claim 5 wherein at least one of the current system characteristics is selected from the group consisting of processor availability for each of the dislike processors, and a data size of data being processed by the software task.
 7. The method as described in claim 1 further comprising: determining that the identified processor has a scheduler for scheduling tasks for the processor; and scheduling the software code to execute on the identified processor, the scheduling including: writing a software code identifier corresponding to the software code to a run queue corresponding to the identified processor.
 8. The method as described in claim 1 further comprising: signaling the identified processor; reading, by the identified processor, the software code from the shared memory into a local memory corresponding to the identified processor; and executing the software code by the identified processor.
 9. The method as described in claim 8 further comprising: writing an instruction block in the shared memory, the instruction block including the address of the loaded software code and the address of an input buffer; and reading the software code and the input buffer from the locations identified in the instruction block to the identified processor's local memory.
 10. The method as described in claim 9 further comprising: signaling the identified processor from one of the other processors, the signaling including: writing the address of the instruction block to a mailbox that corresponds to the identified processor; and reading, by the identified processor, the instruction block in response to the signal.
 11. An information handling system comprising: a plurality of heterogeneous processors; a common memory shared by the plurality of heterogeneous processors; a first processor selected from the plurality of processors that sends a request to a second processor, the second processor also being selected from the plurality of processors; a local memory corresponding to the second processor; a DMA controller associated with the second processor, the DMA controller adapted to transfer data between the common memory and the second processor's local memory; and a loading tool for loading software code to execute on one of the processors, the loading tool including software effective to: identify one of the processors to execute a software task, the identification based upon characteristics of the software task and computing resource availability; loading the software code corresponding to the identified processor into the common memory; and executing the loaded code by the identified processor.
 12. The information handling system as described in claim 11 further comprising software effective to: prior to the identification of one of the processors, a source program compiled into at least two object files, each adapted to be executed on a different processor selected from the plurality of heterogeneous processors, wherein the software code that is loaded and executed is one of the object files.
 13. The information handling system as described in claim 12 further comprising software effective to: analyze the source program for program characteristics; and store the program characteristics.
 14. The information handling system as described in claim 13 wherein at least one of the program characteristics is selected from the group consisting of data locality, computational intensity, and data parallelism.
 15. The information handling system as described in claim 13 wherein identification of the processor further comprises software effective to: retrieve the program characteristics; retrieve current system characteristics, wherein the current system characteristics includes processor load characteristics for the plurality of heterogeneous processors; and combine the program characteristics and the current system characteristics to determine which of the heterogeneous processors to assign the software task.
 16. The information handling system as described in claim 15 wherein at least one of the current system characteristics is selected from the group consisting of processor availability for each of the heterogeneous processors, and a data size of data being processed by the software task.
 17. The information handling system as described in claim 11 further comprising software effective to: determine that the identified processor has a scheduler for scheduling tasks for the processor; and schedule the software code to execute on the identified processor, the schedule including software effective to: write a software code identifier corresponding to the software code to a run queue corresponding to the identified processor.
 18. The information handling system as described in claim 11 further comprising software effective to: signal the identified processor; read, by the identified processor, the software code from the common memory into a local memory corresponding to the identified processor; and execute the software code by the identified processor.
 19. The information handling system as described in claim 18 further comprising software effective to: write an instruction block in the common memory, the instruction block including the address of the loaded software code and the address of an input buffer; and read the software code and the input buffer from the locations identified in the instruction block to the identified processor's local memory.
 20. The information handling system as described in claim 19 further comprising software effective to: signal the identified processor from one of the other processors, the signal including software effective to: write the address of the instruction block to a mailbox that corresponds to the identified processor; and read, by the identified processor, the instruction block in response to the signal.
 21. A computer program product stored on a computer operable media for loading objects in a heterogeneous multiprocessor computer system, said computer program product comprising: means for identifying a processor to execute a software task, the identification based upon characteristics of the software task and computing resource availability; means for loading software code corresponding to the identified processor into a shared memory, wherein the shared memory is shared by a plurality of dislike processors that includes the identified processor; and means for executing the loaded code by the identified processor.
 22. The computer program product as described in claim 21 further comprising: prior to the means for identifying, means for compiling a source program into at least two object files, each adapted to be executed on a different processor selected from the plurality of dislike processors, wherein the software code that is loaded and executed is one of the object files.
 23. The computer program product as described in claim 22 further comprising: means for analyzing the source program for program characteristics; and means for storing the program characteristics.
 24. The computer program product as described in claim 23 wherein at least one of the program characteristics is selected from the group consisting of data locality, computational intensity, and data parallelism.
 25. The computer program product as described in claim 23 wherein the means for identifying the processor further comprises: means for retrieving the program characteristics; means for retrieving current system characteristics, wherein the current system characteristics includes processor load characteristics for the plurality of dislike processors; and means for combining the program characteristics and the current system characteristics to determine which of the dislike processors to assign the software task.
 26. The computer program product as described in claim 25 wherein at least one of the current system characteristics is selected from the group consisting of processor availability for each of the dislike processors, and a data size of data being processed by the software task.
 27. The computer program product as described in claim 21 further comprising: means for determining that the identified processor has a scheduler for scheduling tasks for the processor; and means for scheduling the software code to execute on the identified processor, the means for scheduling including: means for writing a software code identifier corresponding to the software code to a run queue corresponding to the identified processor.
 28. The computer program product as described in claim 21 further comprising: means for signaling the identified processor; means for reading, by the identified processor, the software code from the shared memory into a local memory corresponding to the identified processor; and means for executing the software code by the identified processor.
 29. The computer program product as described in claim 28 further comprising: means for writing an instruction block in the shared memory, the instruction block including the address of the loaded software code and the address of an input buffer; and means for reading the software code and the input buffer from the locations identified in the instruction block to the identified processor's local memory.
 30. The computer program product as described in claim 29 further comprising: means for signaling the identified processor from one of the other processors, the means for signaling including: means for writing the address of the instruction block to a mailbox that corresponds to the identified processor; and means for reading, by the identified processor, the instruction block in response to the signal. 